• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.1
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• pp.1-5
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• 2009

This paper suggests to apply mirror-reflected method based 2D emotion recognition database to 3D application. Also, it makes facial expression of fuzzy modeling using probability of emotion. Suggested facial expression function applies fuzzy theory to 3 basic movement for facial expressions. This method applies 3D application to feature vector for emotion recognition from 2D application using mirror-reflected multi-image. Thus, we can have model based on fuzzy nonlinear facial expression of a 2D model for a real model. We use average values about probability of 6 basic expressions such as happy, sad, disgust, angry, surprise and fear. Furthermore, dynimic facial expressions are made via fuzzy modelling. This paper compares and analyzes feature vectors of real model with 3D human-like avatar.

• The KIPS Transactions:PartD
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• v.9D no.1
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• pp.167-172
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• 2002

Recently, some of people are keep in research and development of the further more efficient and convenient auction systems using intelligent software agents in electronic commerce. The purpose of this thesis is that a simple auction system has web bulletin boards, is aided by intelligent agent, and generates pertinent auction duration time and starting price for auction goods of auctioneer into a auction system, then the auctioneer gets the highest margin. The seller who want to sell goods, is using internet sends mail that has information for goods to agent of internet auction system. The agent undertake filtering process for already learned information about similar goods. And it calculate duration time and start price from stored bidding history database. In this thesis we propose a mailing agent system pushing information in internet auction that enables to aid decision for auctioneer about the starting time and price which delivers the highest margin.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.6
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• pp.493-500
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• 2014

This paper presents findings from the assessment of the volcanic ash fragility for multi-hazard resisting vinyl greenhouse and livestock shed among the agricultural facilities. The volcanic ash fragility was evaluated by using a combination of the FOSM (first-order second-moment) method, available statistics of volcanic load, facility specifications, and building code. In this study, the evaluated volcanic ash fragilities represent the conditional probability of failure of the agricultural facilities over the full range of volcanic ash loads. For the evaluation, 6 types(ie., 2 single span, 2 tree crop, and 2 double span types) of multi-hazard resisting vinyl greenhouses and 3 types(ie., standard, coast, and mountain types) of livestock sheds are considered. All volcanic ash fragilities estimated in this study were fitted by using parameters of the GEV(generalized extreme value) distribution function, and the obtained parameters were complied into a database to be used in future. The volcanic ash fragilities obtained in this study are planning to be used to evaluate risk by volcanic ash when Mt. Baekdu erupts.

• Journal of the Korean GEO-environmental Society
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• v.13 no.8
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• pp.25-33
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• 2012

Although it is important to reflect the accurate information of the ground condition in the tunnel design, the analysis and design are conducted by limited information because it is very difficult to consider various geographies and geotechnical conditions. When the tunnel is under construction, examination of accurate safety and prediction of behavior are overcome the limits of predicting behavior by Artificial Neural Network in this study. First, construct the suitable structure after the data of field was made sure by the multi-layer back propagation, then apply with algorithm. Employ the result of measured data from database, and consider the influence factor of tunnel, like supporting pattern, RMR, Q, the types of rock, excavation length, excavation shape, excavation over, to carry out the reliable analysis through field applicability of Artificial Neural Network. After studying, using the ANN model to predict the shearing displacement, convergence displacement, underground displacement, Rock bolt output follow the excavation over of tunnel construction field, then determine the field applicability with ANN through field measured value and comparison analysis when tunnel is being constructed.

• Journal of KIISE:Software and Applications
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• v.34 no.7
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• pp.585-594
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• 2007

The back propagation algorithm took a long time to learn the input patterns and was difficult to train the additional or repeated learning patterns. So Aleksander proposed the binary neural network which could overcome the disadvantages of BP Network. But it had the limitation of repeated learning and was impossible to extract a generalized pattern. In this paper, we proposed a dynamic 3 dimensional Neuro System which was consisted of a learning network which was based on weightless neural network and a feedback module which could accumulate the characteristic. The proposed system was enable to train additional and repeated patterns. Also it could be produced a generalized pattern by putting a proper threshold into each learning-net's discriminator which was resulted from learning procedures. And then we reused the generalized pattern to elevate the recognition rate. In the last processing step to decide right category, we used maximum response detector. We experimented using the MNIST database of NIST and got 99.3% of right recognition rate for training data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.1
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• pp.108-114
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• 2008

Since flash memory cannot be overwritten, new data are updated in new area. If data are frequently updated, garbage collection which is achieved by erasing blocks, should be performed to reclaim new area. Hence, because the count of erase operations is limited due to characteristics of flash memory, every block should be evenly written and erased. However, if data with access locality are processed by cost benefit algorithm with separation of hot block ad cold block though the performance of processing is hight wear-leveling is not even. In this paper, we propose CB-MB (Cost Benefit between Multi Bank) algorithm in which hot data are allocated in one bank and cold data in another bank, and in which role of hot bank and cold bank is exchanged every period. CB-MB shows that its performance is 30% better than cost benefit algorithm with separation of cold block and hot block its wear-leveling is about a third of that in standard deviation.

• Journal of Korean Medical Science
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• v.33 no.43
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• pp.239.1-239.12
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• 2018

Background: We described a novel multi-step retinal fundus image reading system for providing high-quality large data for machine learning algorithms, and assessed the grader variability in the large-scale dataset generated with this system. Methods: A 5-step retinal fundus image reading tool was developed that rates image quality, presence of abnormality, findings with location information, diagnoses, and clinical significance. Each image was evaluated by 3 different graders. Agreements among graders for each decision were evaluated. Results: The 234,242 readings of 79,458 images were collected from 55 licensed ophthalmologists during 6 months. The 34,364 images were graded as abnormal by at-least one rater. Of these, all three raters agreed in 46.6% in abnormality, while 69.9% of the images were rated as abnormal by two or more raters. Agreement rate of at-least two raters on a certain finding was 26.7%-65.2%, and complete agreement rate of all-three raters was 5.7%-43.3%. As for diagnoses, agreement of at-least two raters was 35.6%-65.6%, and complete agreement rate was 11.0%-40.0%. Agreement of findings and diagnoses were higher when restricted to images with prior complete agreement on abnormality. Retinal/glaucoma specialists showed higher agreements on findings and diagnoses of their corresponding subspecialties. Conclusion: This novel reading tool for retinal fundus images generated a large-scale dataset with high level of information, which can be utilized in future development of machine learning-based algorithms for automated identification of abnormal conditions and clinical decision supporting system. These results emphasize the importance of addressing grader variability in algorithm developments.

• International Area Studies Review
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• v.12 no.2
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• pp.27-53
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• 2008

This paper investigates factors determining the level of nontraditional activities at banks around the world. Specifically, the paper examines what kinds of firm-specific and country-specific characteristics determine the level of noninterest income using a comprehensive multi-country database. This paper focuses beyond the traditional U.S. based analyses and provides detailed asset-liability management practices of banks around the world.The findings suggest that banks' size and loan loss provision, explicit deposit insurance, banking restriction, banking freedom ranking of respective countries, the extent of state and foreign ownership, governance, and transparency of the country have positive effects on the level of nontraditional activities. Greater dependence on traditional lending and financing, market based economy, and multiple bank supervisory bodies in the country have negative associations with noninterest income. The economic development of country however affects the extent of the relationship.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.5
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• pp.789-798
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• 2021

In this study, for the purpose of collecting and analyzing target-specific RCS data of target signals simulator for verification/improvement of radar system performance, VHF band monostatic/bistatic RCS of civil aircraft(B-747, B-737) and fighter(F-16) models were analyzed by EM simulation tool. In order to reduce the RCS analysis time, the analysis time and RCS data were compared and cross-verified. Also, the analysis range was selected by examining the interpolation error according to the analysis angle resolution. The RCS data obtained for each model were analyzed separately by the incident/reflection elevation angle and frequency. The RCS characteristics according to the shape of the aircraft and the incident/reflection azimuth angle were described. Finally, the statistical RCS distribution value of each model is presented through RCS distribution histogram analysis. In the future, the RCS database obtained by this study will be used for the target signals simulator of the VHF band radar system.

• Journal of Convergence for Information Technology
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• v.10 no.12
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• pp.216-225
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• 2020

This study was conducted to qualitatively analyze the selected research through a systematic review to find out application method, outcome measures, and intervention effects of dual task. We searched for published studies from January 2010 to December 2019. Electrical database were PubMed and ProQuest. Search terms were 'dual task' OR 'multi modal' AND 'mild cognitive impairment' OR 'dementia' OR 'Alzheimer's disease'AND 'intervention' OR 'rehabilitation. There were 8 studies selected finally. The dual task was applied not as a single intervention but as a combined intervention with other exercises. The contents of dual task were consisted of motor and cognitive tasks to be independent each other. The outcome measures included general cognitive function such as MMSE and CERAD, executive function, and memory. Additionally the dual task cost was also used to identify the direct improvement of the dual task. This study could provide informations of dual task application on elderly with cognitive impairment.